Wavefront algorithms are algorithms on grids where execution proceeds in a wavefront manner from the start to the end of the execution (execution moves through the grid as if a wavefront is moving). Many dynamic programming problems and stencil computations are wavefront algorithms. Iterative wavefront algorithms for evaluating dynamic programming (DP) recurrences exploit optimal parallelism, b...

A method for automatic 2D image registration based on combining multiple row-wise and column-wise dynamic programming (DP) processes is presented. Combination is performed by means of a parametric transform (either rigid or non-rigid) which is estimated from the output of the dynamic programming processes. The method performs particularly well on histopathology images as dynamic programming is ...

This paper presents a formalization of the energy management problem in hybrid electric vehicles and a comparison of three known methods for solving the resulting optimization problem. Dynamic programming (DP), Pontryagin’s minimum principle (PMP), and equivalent consumption minimization strategy (ECMS) are described and analyzed, showing formally their substantial equivalence. Simulation resul...

Neural networks have recently been shown to be a very effective approach to the unconstrained segmentation of speech into phoneme-like units. The neural network is trained to indicate when a short local sequence of feature vectors is associated with a segment boundary, and when it is not. Although this approach delivers state-of-the-art performance, it is prone to over-segmentation at ambiguous...

Prosody structure prediction plays an important role in text-tospeech (TTS) conversion systems. It is the must and prior step to parametric prosody prediction. Dynamic programming (DP) and decision tree (DT) are widely used for prosody structure prediction [1][2][3] but with well-known limitations. In this paper, two other new methods, combination of dynamic programming with decision tree and c...

2 Consider a batch-sizing problem, where all jobs are identical or similar, and a unit processing time (1  p) is specified for each job. To minimize the total completion time of jobs, partitioning jobs into batches may be necessary. Learning effect from setup repetition makes small-sized batches; on the contrary, job's learning effect results in large-sized batches. With their collaborative in...

For pitch tracking of a single speaker, a common requirement is to find the optimal path through a set of voiced or voiceless pitch estimates over a sequence of time frames. Dynamic programming (DP) algorithms have been applied before to this problem. Here, the pitch candidates are provided by a multi-channel autocorrelation-based estimator, and DP is extended to pitch tracking of multiple conc...

The Knapsack Problem with Setup (KPS) is a generalization of the classical Knapsack problem (KP), where items are divided into families. An individual item can be selected only if a setup is incurred for the family to which it belongs. This paper provides a dynamic programming (DP) algorithm for the KPS that produces optimal solutions in pseudo-polynomial time. In order to reduce the storage re...

A spine x-ray image retrieval system has been developed for retrieving images based on the pathology information such as the osteophyte. Osteophyte shows only in particular regions on the vertebra. This means the contour information on the vertebra regions that are not of interest hinder the image retrieval relevance precision. Curve matching or partial shape matching (PSM) methods based on dyn...

In this paper, we describe a search procedure for statistical machine translation (MT) based on dynamic programming (DP). Starting from a DP-based solution to the traveling salesman problem, we present a novel technique to restrict the possible word reordering between source and target language in order to achieve an eÆcient search algorithm. A search restriction especially useful for the trans...